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Optimize attempts in a timed logic test

Last updated: Mar 29, 2026

Quick Overview

This question evaluates a candidate's understanding of expected value, time-constrained optimization, efficiency metrics (score per second), and discrete decision-making under uncertainty when allocating time across heterogeneous items.

  • medium
  • Shopify
  • Statistics & Math
  • Data Scientist

Optimize attempts in a timed logic test

Company: Shopify

Role: Data Scientist

Category: Statistics & Math

Difficulty: medium

Interview Round: HR Screen

A timed OA section has 25 minutes (1,500 seconds) and 30 questions: 21 Easy logic items (each takes 45s, accuracy=90%) and 9 Hard items (each takes 75s, accuracy=70%). Scoring: +3 correct, 0 blank, –1 wrong. You may choose which items to attempt and cannot return to questions once skipped. a) If you attempt all Easy first, then as many Hard as time allows, how many items do you attempt and what is your expected total score? b) Compute expected score per second for Easy vs. Hard and use it to justify the ordering. c) Suppose spending an extra 15s on each Hard raises its accuracy to 78% (so Hard now takes 90s for accuracy=78%). Within the same 1,500s budget and still doing all Easy first, is it optimal to invest the extra time on Hard? Show the optimal mix and expected score, and reconcile your conclusion with the per-second efficiency numbers (note the discrete time constraint).

Quick Answer: This question evaluates a candidate's understanding of expected value, time-constrained optimization, efficiency metrics (score per second), and discrete decision-making under uncertainty when allocating time across heterogeneous items.

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Timed OA: Maximize Expected Score Under a Time Limit

Context: You have 25 minutes (1,500 seconds) to attempt up to 30 multiple-choice items. You may choose which items to attempt; once you skip a question, you cannot return. Scoring is +3 for a correct answer, 0 for blank, and −1 for a wrong answer.

Item types:

  • Easy: 21 items; 45 seconds each; 90% accuracy.
  • Hard: 9 items; 75 seconds each; 70% accuracy.

Tasks:

  • (a) If you attempt all Easy first, then as many Hard as time allows, how many items do you attempt and what is your expected total score?
  • (b) Compute expected score per second for Easy vs. Hard and use it to justify the ordering.
  • (c) Suppose spending an extra 15 seconds on each Hard raises its accuracy to 78% (so Hard now takes 90s for 78% accuracy). Within the same 1,500s budget and still doing all Easy first, is it optimal to invest the extra time on Hard? Show the optimal mix and expected score, and reconcile your conclusion with the per-second efficiency numbers (note the discrete time constraint).

Solution

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